0000000000714068

AUTHOR

Maria Grazia Peninno

0000-0002-7577-2617

Small changes, big impacts: Geographic expansion in small-scale fisheries

Abstract Small-scale fisheries are an important, yet neglected, millenarian activity that has been undergoing significant changes that threaten its future. Understanding how this activity is spatially distributed and the factors that drive its use of the marine space over time can shed some light on how fishing efforts and their impacts have moved over different parts of coastal marine ecosystems. This study investigated changes to the spatial distribution of small-scale fisheries along the Brazilian equatorial region between 1994 and 2014 and the factors, from ecological to socioeconomic, that influenced this shift. Bayesian hierarchical spatial models were used together with environmental…

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Seasonality of spatial patterns of abundance, biomass and biodiversity in a demersal community of the NW Mediterranean Sea

14 pages, 5 figures, 4 tables

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Identifying the best fishing-suitable areas under the new European discard ban

Abstract The spatial management of fisheries has been repeatedly proposed as a discard mitigation measure. A number of studies have assessed the fishing suitability of an area based on units of by-catch or discard per unit effort. However, correct identification of fishing-suitable areas should assess biomass loss with respect to the benefits. This study therefore, proposes the analysis of by-catch ratios, which do represent benefit vs. loss and are standardized to a wide range of effort characteristics. Furthermore, our study proposes the use of two ratios: the proportion of total unwanted biomass out of the total catch as an indicator of the overall ecological impact, and the proportion o…

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A spatially explicit risk assessment approach: Cetaceans and marine traffic in the Pelagos Sanctuary (Mediterranean Sea).

15 páginas, 5 figuras, 2 tablas.-- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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The Bias of combining variables on fish's aggressive behavior studies.

Made available in DSpace on 2019-10-06T16:27:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-01 Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive …

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Fishery-dependent and -independent data lead to consistent estimations of essential habitats

AbstractSpecies mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Es…

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Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach

In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator spe…

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Accounting for preferential sampling in species distribution models

D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…

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Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution

Abstract Worldwide, cetacean species have started to be protected, but they are still very vulnerable to accidental damage from an expanding range of human activities at sea. To properly manage these potential threats we need a detailed understanding of the seasonal distributions of these highly mobile populations. To achieve this goal, a growing effort has been underway to develop species distribution models (SDMs) that correctly describe and predict preferred species areas. However, accuracy is not always easy to achieve when physical barriers, such as islands, are present. Indeed, SDMs assume, if only implicitly, that the spatial effect is stationary, and that correlation is only depende…

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Small-scale shrimp fisheries bycatch: a multi-criteria approach for data-poor situations

Abstract Bycatch and discards from small-scale fisheries (SSF) are usually ignored when compared with industrial fisheries, not only by policy-makers, but also by scientists. Therefore, SSF social, economic and ecological impacts are poorly known and especially in the context of incidental catches, regardless of whether they become bycatch or discards. Such neglect is worrisome due to the role that SSF play in food security and poverty alleviation, particularly in coastal and rural communities in developing countries. In this study, a combination of sampling data and the fishers' behavior (specifically the basis of their decision on where to fish) were used. Bayesian models were applied to …

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